We performed a comparison between Amazon EC2 and Apache Spark based on real PeerSpot user reviews.
Find out in this report how the two Compute Service solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."What we have found most valuable is that we have not lost stability in the program."
"I believe that cloud solutions are better than physical servers."
"The scalability of the solution is fantastic. It's one of our favorite features."
"The scalability of Amazon EC2 is good. However, the stability can depend on what service I am using."
"The ability to quickly spin up instances on demand with zero upfront costs or infrastructure is the most valuable for me."
"The Key Management Service (KMS) feature is very helpful for security. It encrypts the data that is being saved. Cloud storage is also very helpful, and it could be AWS S3, which a lot of people use."
"My favorite feature of this solution is the flexibility of instance types, which allows for the cost to be tailored to the usage amount and type."
"The most valuable features are the scalability options, low maintenance, and options to upgrade. AWS support is also pretty good. The generation upgrade is pretty simple and standardized."
"The most valuable feature of this solution is its capacity for processing large amounts of data."
"I like that it can handle multiple tasks parallelly. I also like the automation feature. JavaScript also helps with the parallel streaming of the library."
"Now, when we're tackling sentiment analysis using NLP technologies, we deal with unstructured data—customer chats, feedback on promotions or demos, and even media like images, audio, and video files. For processing such data, we rely on PySpark. Beneath the surface, Spark functions as a compute engine with in-memory processing capabilities, enhancing performance through features like broadcasting and caching. It's become a crucial tool, widely adopted by 90% of companies for a decade or more."
"We use it for ETL purposes as well as for implementing the full transformation pipelines."
"Spark can handle small to huge data and is suitable for any size of company."
"Provides a lot of good documentation compared to other solutions."
"The good performance. The nice graphical management console. The long list of ML algorithms."
"Spark helps us reduce startup time for our customers and gives a very high ROI in the medium term."
"Regional acceleration could improve. If I am hosting a website and I want the experience to be faster they should have this feature to allow for increased speeds."
"The IP changes whenever we restart which is frustrating."
"Regional acceleration could improve. If I am hosting a website and I want the experience to be faster they should have this feature to allow for increased speeds."
"I think the pricing needs to be adjusted and better security."
"The GUI used to deploy EC2 must be improved."
"They should fix the key pair name functionality and provide the ability to assign multiple key pair names to an EC2 instance. It is a key pair feature, and it provides you the ability to actually log into the server. It is basically like a password. In terms of new features, it should have the ability to increase and decrease the instance size based on certain times of the day. We should be able to do this without turning off the EC2 instance. Currently, you have to turn it off and then turn it back on. It should also have HTTPS or SSL integration."
"Built-in and/or integration with other services to proactively identify potential failures before they occur."
"My impression is that the scalability of this product could be improved. My opinion is that, for example, the Lambda solution is much more scalable than EC2."
"Apache Spark's GUI and scalability could be improved."
"It needs a new interface and a better way to get some data. In terms of writing our scripts, some processes could be faster."
"We use big data manager but we cannot use it as conditional data so whenever we're trying to fetch the data, it takes a bit of time."
"The management tools could use improvement. Some of the debugging tools need some work as well. They need to be more descriptive."
"Apart from the restrictions that come with its in-memory implementation. It has been improved significantly up to version 3.0, which is currently in use."
"Apache Spark is very difficult to use. It would require a data engineer. It is not available for every engineer today because they need to understand the different concepts of Spark, which is very, very difficult and it is not easy to learn."
"There could be enhancements in optimization techniques, as there are some limitations in this area that could be addressed to further refine Spark's performance."
"It would be beneficial to enhance Spark's capabilities by incorporating models that utilize features not traditionally present in its framework."
Amazon EC2 is ranked 3rd in Compute Service with 60 reviews while Apache Spark is ranked 5th in Compute Service with 60 reviews. Amazon EC2 is rated 8.6, while Apache Spark is rated 8.4. The top reviewer of Amazon EC2 writes "Easy to scale and valuable features include the security group and key management". On the other hand, the top reviewer of Apache Spark writes "Reliable, able to expand, and handle large amounts of data well". Amazon EC2 is most compared with AWS Fargate, AWS Lambda, AWS Batch and Apache NiFi, whereas Apache Spark is most compared with Spring Boot, AWS Batch, Spark SQL, SAP HANA and Jakarta EE. See our Amazon EC2 vs. Apache Spark report.
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We monitor all Compute Service reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
